The present invention relates to an image processing method and apparatus, and more particularly, to a method and apparatus for extracting an image, which meets a predetermined condition, from among a plurality of images.
Medical images are helpful in diagnosing a patient condition. Medical images provide unique information depending on what modality is used to produce the medical images. Medical images produced by an appropriate modality are employed according to a purpose of diagnosis.
In order to given more appropriate diagnosis on the basis of diverse information, a plurality of kinds of medical images produced by a plurality of modalities, such as, an X-ray computed tomography (CT) apparatus, a magnetic resonance imaging (MRI) apparatus, and a positron emission tomography (PET) apparatus or a single photon emission computed tomography (SPECT) apparatus are employed.
For example, the X-ray CT apparatus and PET apparatus are used to image the same region of the same patient. Images produced by the X-ray CT apparatus and showing the structure of the cerebral parenchyma, and images produced by the PET apparatus and showing the active state of the brain are used to diagnose a lesion in terms of the structure of the lesion and the function thereof. At this time, a synthetic image produced by superposing two different kinds of images in order to facilitate simultaneous grasping of the structure and function.
In order to produce such a synthetic image, two images are aligned with each other. The alignment may be referred to as registration. The registration is performed by a computer.
For the registration, a technique described in, for example, “Multi-modal Volume Registration by Maximization of Mutual Information” written by W. M. Wells III et al. is adopted.
Generally speaking, the registration is achieved through transformation through which the amount of mutual information and a candidate image v(x) shares with a reference image u(x) is maximized. Namely,
                              T          ^                =                  arg          ⁢                                                                                ⁢              max                        T                    ⁢                                          ⁢                      I            ⁡                          (                                                u                  ⁡                                      (                    x                    )                                                  ,                                  v                  ⁡                                      (                                          T                      ⁡                                              (                        x                        )                                                              )                                                              )                                                          (        1        )            where T denotes the transformation from the apparatus of coordinates for the candidate image to the apparatus of coordinates for the reference image.I(u(x), v(T(x)))  (2)The formula 2 denotes mutual information.I(u(x), v(T(x)))≡h(u(x))+h(v(T(x)))−h(u(x), v(T(x)))  (3)where h(•) denotes an entropy.h(x)≡−∫p(x)In p(x)dx  (4)h(x,y)≡−∫p(x,y)In p(x,y)dxdy  (5)The above formulae provide an entropy.
The foregoing registration proves effective when it is previously apparent that two images result from visualization of the same region. Otherwise, even if transformation provides an image that shares the largest amount of mutual information with a reference image, the transformation does not always lead to significant registration.